Predicting Uncertainty in Geometric Fluid Mechanics
classification
🌊 nlin.CD
physics.flu-dyn
keywords
fluidgeometricmechanicsmotionscalescomputationallydatadata-driven
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We review opportunities for stochastic geometric mechanics to incorporate observed data into variational principles, in order to derive data-driven nonlinear dynamical models of effects on the variability of computationally resolvable scales of fluid motion, due to unresolvable, small, rapid scales of fluid motion.
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